
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
     from ... import FeatureExtractionMixin, TensorType

lowerCamelCase__     :		str        = logging.get_logger(__name__)

lowerCamelCase__     :		Dict        = {
    """openai/imagegpt-small""": """""",
    """openai/imagegpt-medium""": """""",
    """openai/imagegpt-large""": """""",
}



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Tuple	   =      'imagegpt'
 __lowerCAmelCase	:  Tuple	   =      ['past_key_values']
 __lowerCAmelCase	:  str	   =      {
     'hidden_size': 'n_embd',
     'max_position_embeddings': 'n_positions',
     'num_attention_heads': 'n_head',
     'num_hidden_layers': 'n_layer',
 }


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=5_12 + 1       ,	SCREAMING_SNAKE_CASE_=32 * 32       ,	SCREAMING_SNAKE_CASE_=5_12       ,	SCREAMING_SNAKE_CASE_=24       ,	SCREAMING_SNAKE_CASE_=8       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_="quick_gelu"       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=1E-5       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=True       ,	SCREAMING_SNAKE_CASE_=False       ,	SCREAMING_SNAKE_CASE_=False       ,	SCREAMING_SNAKE_CASE_=False       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   lowercase__	: Any     		=   vocab_size
   lowercase__	: Optional[Any]     		=   n_positions
   lowercase__	: List[str]     		=   n_embd
   lowercase__	: Tuple     		=   n_layer
   lowercase__	: Optional[Any]     		=   n_head
   lowercase__	: List[str]     		=   n_inner
   lowercase__	: Union[str, Any]     		=   activation_function
   lowercase__	: Union[str, Any]     		=   resid_pdrop
   lowercase__	: Optional[int]     		=   embd_pdrop
   lowercase__	: int     		=   attn_pdrop
   lowercase__	: str     		=   layer_norm_epsilon
   lowercase__	: Optional[Any]     		=   initializer_range
   lowercase__	: Any     		=   scale_attn_weights
   lowercase__	: str     		=   use_cache
   lowercase__	: str     		=   scale_attn_by_inverse_layer_idx
   lowercase__	: Optional[int]     		=   reorder_and_upcast_attn
   lowercase__	: Union[str, Any]     		=   tie_word_embeddings

   super().__init__(tie_word_embeddings=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_)



class    _snake_case (						UpperCAmelCase_				):


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   return OrderedDict(
       [
           ("""input_ids""", {0: """batch""", 1: """sequence"""}),
       ])



 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = 1       ,	SCREAMING_SNAKE_CASE_ = -1       ,	SCREAMING_SNAKE_CASE_ = False       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = 3       ,	SCREAMING_SNAKE_CASE_ = 32       ,	SCREAMING_SNAKE_CASE_ = 32       ,	):


   '''simple docstring'''




   lowercase__	: List[Any]     		=   self._generate_dummy_images(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)
   lowercase__	: Optional[Any]     		=   dict(preprocessor(images=SCREAMING_SNAKE_CASE_       ,	return_tensors=SCREAMING_SNAKE_CASE_))

   return inputs










"""simple docstring"""



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{'vocab_file': 'vocab.txt'}

lowercase_							=							{
    'vocab_file': {
        'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/vocab.txt',
        'YituTech/conv-bert-medium-small': (
            'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/vocab.txt'
        ),
        'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/vocab.txt',
    }
}

lowercase_							=							{
    'YituTech/conv-bert-base': 5_12,
    'YituTech/conv-bert-medium-small': 5_12,
    'YituTech/conv-bert-small': 5_12,
}


lowercase_							=							{
    'YituTech/conv-bert-base': {'do_lower_case': True},
    'YituTech/conv-bert-medium-small': {'do_lower_case': True},
    'YituTech/conv-bert-small': {'do_lower_case': True},
}







class    __a						( __snake_case							):
				lowerCamelCase     :       Optional[int]			       =VOCAB_FILES_NAMES
				lowerCamelCase     :       List[str]			       =PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase     :       str			       =PRETRAINED_INIT_CONFIGURATION
				lowerCamelCase     :       Any			       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase     :       List[str]			       =ConvBertTokenizer







				def __init__( self      ,	UpperCAmelCase=None      ,	UpperCAmelCase=None      ,	UpperCAmelCase=True      ,	UpperCAmelCase="[UNK]"      ,	UpperCAmelCase="[SEP]"      ,	UpperCAmelCase="[PAD]"      ,	UpperCAmelCase="[CLS]"      ,	UpperCAmelCase="[MASK]"      ,	UpperCAmelCase=True      ,	UpperCAmelCase=None      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					super().__init__(
					    UpperCAmelCase      ,	tokenizer_file=UpperCAmelCase      ,	do_lower_case=UpperCAmelCase      ,	unk_token=UpperCAmelCase      ,	sep_token=UpperCAmelCase      ,	pad_token=UpperCAmelCase      ,	cls_token=UpperCAmelCase      ,	mask_token=UpperCAmelCase      ,	tokenize_chinese_chars=UpperCAmelCase      ,	strip_accents=UpperCAmelCase      ,	**UpperCAmelCase      ,	)

					lowerCAmelCase_      							=			json.loads(self.backend_tokenizer.normalizer.__getstate__()   )
					if (
					    normalizer_state.get('''lowercase'''      ,	UpperCAmelCase   ) != do_lower_case
					    or normalizer_state.get('''strip_accents'''      ,	UpperCAmelCase   ) != strip_accents
					    or normalizer_state.get('''handle_chinese_chars'''      ,	UpperCAmelCase   ) != tokenize_chinese_chars
					):
						lowerCAmelCase_      							=			getattr(UpperCAmelCase      ,	normalizer_state.pop('''type'''   )   )
						lowerCAmelCase_      							=			do_lower_case
						lowerCAmelCase_      							=			strip_accents
						lowerCAmelCase_      							=			tokenize_chinese_chars
						lowerCAmelCase_      							=			normalizer_class(**UpperCAmelCase   )

					lowerCAmelCase_      							=			do_lower_case







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase=None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			[self.cls_token_id] + token_ids_a + [self.sep_token_id]

					if token_ids_a:
						output += token_ids_a + [self.sep_token_id]

					return output







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase = None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			[self.sep_token_id]
					lowerCAmelCase_      							=			[self.cls_token_id]
					if token_ids_a is None:
						return len(cls + token_ids_a + sep   ) * [0]
					return len(cls + token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1]







				def      lowerCamelCase_     ( self      ,	UpperCAmelCase      ,	UpperCAmelCase = None   ):

					'''simple docstring'''






					lowerCAmelCase_      							=			self._tokenizer.model.save(UpperCAmelCase      ,	name=UpperCAmelCase   )
					return tuple(UpperCAmelCase   )